Modern danger detectors have achieved a sensitivity with regard to the detection of danger parameters that that the main problem is no longer the detection of a danger parameter as early as possible, but to distinguish reliably interference signals from true danger signals and thereby avoid false alarms. Danger signals and interference signals are distinguished substantially by using a plurality of different sensors and correlating their signals or by analyzing various features of the signals of a single sensor and/or by appropriate signal processing. A substantial improvement in interference immunity has already been achieved recently by using fuzzy logic.
Fuzzy logic is generally known. With regard to the evaluation of the signals of danger detectors, it is to be emphasized that signal values are allocated to fuzzy sets in accordance with a membership function. The value of the membership function, or the degree of membership of a fuzzy set, is between 0 and 1. It is important that the membership functions can be normalized, i.e. the sum of all the values of the membership function is equal to one, as a result of which the fuzzy logic evaluation permits an unambiguous interpretation of the signals.